If you need data off the web on an ongoing basis, the vendor you want isn't the one who can pull a table today — almost anyone can. It's the one whose scraper is still delivering clean data next quarter, after the target site redesigned its markup, added a bot wall, and started rate-limiting your IPs. A one-off scrape of a cooperative site starts around $2k; a monitored pipeline that has to keep running is a retainer, realistically from $3k a month, because you're buying a data feed that survives a moving target, not a script.
That distinction is the whole decision, and it's invisible in a quick proof of concept. Below is what to look for in a scraping partner, an honest comparison of a cheap freelancer versus an off-the-shelf data provider versus a specialist studio, real cost ranges, why scrapers break and why the sane structure is a retainer, and where Duskel fits. If you want the pricing angle in depth, we wrote a companion piece on what a web scraping service costs.
What to look for in a web scraping company
You're not hiring someone to extract text — that's the easy hour. You're hiring for everything that keeps the extraction working against a site that would rather you didn't. A good partner raises these before you do:
- Reliability against anti-bot defenses. CAPTCHAs, fingerprinting, behavioral detection, and outright IP bans are the norm on anything worth scraping at scale. Ask how they handle them, how they degrade when a wall goes up, and how they avoid getting your whole operation blocked — not whether they can bypass everything, which nobody honestly can.
- Proxy and IP strategy. Defended sites at volume need rotating and often residential IPs, and those are a real recurring cost that scales with how much you pull. A vendor who never mentions proxies is either scraping something trivial or hasn't hit the wall yet.
- Schema-drift handling. Sites change their HTML without warning and your selectors evaporate. The right answer isn't "we'll fix it when you notice the data stopped" — it's isolating every DOM assumption, validating output shape on every run, and failing loudly the moment the structure shifts.
- Monitoring and alerting. A scraper that silently returns nothing is worse than one that crashes, because you trust the empty result. You want checks on volume, freshness, and field completeness that page a human when the numbers look wrong — before your dashboards quietly go stale.
- Data quality as a deliverable. Raw scraped data is messy: duplicates, half-loaded pages, inconsistent formats, missing fields. Cleaning, deduplicating, validating, and structuring it is often more work than the scrape and it's what decides whether the exercise was worth anything.
- Legal and terms-of-service care. A serious partner asks what you're collecting and how you'll use it, checks whether an official API or data-licensing option exists, and flags terms-of-service and jurisdictional constraints early — rather than pretending they don't exist and handing you the risk.
Freelancer vs data provider vs specialist studio
There are three ways to buy web data, and they fail in different places. The cheap freelancer is fine until the site fights back. The off-the-shelf data provider is great when they already sell exactly your dataset and useless when you need something bespoke. The specialist studio costs more upfront and earns it on everything that has to keep running. Here's an honest read against what actually matters.
| What matters | Cheap freelancer | Off-the-shelf data provider | Specialist studio |
|---|---|---|---|
| Reliability | Works on cooperative sites; stalls the moment anti-bot walls or JS rendering appear | High for datasets they already sell; no help for anything custom | Built for defended, JS-heavy, changing targets — with graceful degradation |
| Maintenance | Usually ships and moves on; you notice the break, not them | Handled for you, but only for their catalog on their schedule | Ongoing: re-fix selectors, rotate proxies, adapt as the target shifts |
| Compliance | Rarely raised; risk lands on you | Vetted for their own dataset; standard terms | Raised early — API check, ToS and jurisdiction flagged before work starts |
| Cost | Lowest sticker price; highest total cost once it breaks | Per-record or subscription; efficient if the data exists off the shelf | Higher upfront; priced as a retainer for a feed that keeps working |
| Best when | A one-off pull from a static, cooperative site | A common dataset someone already packages and sells | Bespoke, ongoing extraction that a business process depends on |
A cheap scrape is cheap until the site changes; then you find out what you didn't pay for.
The order to check them is right-to-left on cost: see if a data provider or an official API already sells what you need — it's often cheaper than building anything. If the data is bespoke or the source is yours to defend, that's specialist work.
What it costs
Cost is driven by how hard the site fights back and whether you need the data once or forever — not by the data itself. Here's roughly how the tiers land in 2026, split between a one-off scrape and a monitored pipeline you keep on retainer.
| Complexity | One-off scrape | Monitored pipeline (retainer) | What it looks like |
|---|---|---|---|
| Simple | From $2k | From $3k/mo | Static pages, predictable structure, few or no defenses, modest volume. A one-time pull is genuinely all a lot of projects need; the retainer only makes sense if you want it refreshed on a schedule. |
| Medium | $4k–$8k | $3k–$6k/mo | Scheduled scraping of sites with some defenses and JS-rendered content. Needs proxy rotation, retry logic, and monitoring that tells you when a site changes and the data stops flowing. |
| Complex | Case by case | $6k/mo+ | Large-scale or many-source extraction from sites that fight hard, feeding a pipeline other systems depend on. Serious anti-bot handling, high volume, tight data-quality rules, and near-constant upkeep. |
Ranges are indicative; the recurring cost of keeping a live scraper alive dwarfs the one-time build.
Two line items hide in cheap quotes. Infrastructure — proxies, residential IPs, and CAPTCHA solving where needed — is a recurring cost that scales with volume. And maintenance is the big one: a scraper decays the moment the target updates its HTML, so a low flat fee with no upkeep plan is a scraper priced to break. We wrote up the full cost picture separately if you want the detail.
Why scrapers break — and why a retainer, not a one-off
A scraper isn't a finished artifact; it's a thing that decays. The reasons are boringly predictable, which is exactly why they should be planned for rather than treated as surprises:
- Layout changes. A redesign, an A/B test, or a framework upgrade rewrites the HTML and your selectors point at nothing.
- Escalating defenses. Sites add or tighten anti-bot systems over time; what sailed through last month gets challenged or blocked this month.
- IP and rate-limit pressure. Volume that was tolerated gets throttled or banned, and the proxy pool that worked needs rotating or expanding.
- Silent partial failures. A page half-loads, a field moves, or JavaScript renders late, and you get plausible-looking data that's quietly wrong — the most dangerous failure of all.
Because the target keeps moving, ongoing scraping is a monthly engagement, not a fixed-price delivery. The build is a fraction of the real cost; the value is in the maintenance, the monitoring that catches a break the day it happens, and the proxies and infrastructure that keep running. A retainer is simply honest pricing for a live feed. A one-off makes sense only when you truly need the data once and can tolerate it going stale.
Why Duskel — data that keeps flowing
We build scraping systems for the part that isn't the demo: staying reliable after the site changes and starts pushing back. That means proxy and IP strategy sized to the target, output validation and monitoring that fail loudly the moment structure drifts or volume drops, and data cleaning handed over as a real deliverable rather than a pile of messy rows. We're a studio that ships and maintains production software, so a scraper we hand you is built to the standard we hold our own systems to — instrumented, monitored, and maintained.
We're also honest about the parts that constrain you. We check whether an official API or data-licensing option already exists before quoting a scrape, and we raise the terms-of-service and legal picture for your specific use up front — because the cheapest scraper in the world isn't cheap if it collects data you weren't allowed to collect. No fabricated case studies here; tell us what data you need and where it lives and we'll scope the scrape, the compliance questions, and the maintenance honestly.